Motivation

Figure 1 shows that 444 municipalities of the region lost more than 20% of their population in the last two decades (in red):

Objectives

• General: The Construction of a Spatial Depopulation Risk Index (SDRI) using spatial Principal Component Analysis to ranking the municipalities of Castilla-La Mancha.
• Secondaries:
  • To detect spatial dependence of depopulation in Castilla-La Mancha.
  • To calculate the range of the spatial dependence.
  • To include the spatial dependence in a depopulation risk index.
  • To rank the municipalities of Castilla-La Mancha in terms of risk depopulation in order to identify areas in which counter-measures can be applied.

Methods

ENTIENDO QUE LO HAS PUESTO DE EJEMPLO.

Igual que en almagro: - Geoestadística y semivariograma. - Spatial PCA

Spatial dependence is checked with Moran’s I:

\[ I= \frac{N}{\sum _{i}\sum _{j} w_{ij}} \frac {\sum _{i}\sum _{j} w_{ij} (X_i - \bar{X}) (X_j - \bar{X})} {\sum _{i} (X_i - \bar{X})^2} \]

Range of spatial dependence is extracted from the semivariogram, the heart of Geostatistics, which is a tool that catch the spatial dependence according to the distance (see Figure 2): The semivariogram is the heart of Geostatistics

Results

Ideas:

• Data

• Mapa de sPCA depenencia y autovalores

• Lollipop

Conclusions

References

Jombart, T.; Devillard, S.; Dufour, A.-B.; Pontier, D. Revealing cryptic spatial patterns in genetic variability by a new multivariate method, Heredity, 101 (2008), 92-103.